Driver Engineer

About Modular

About the role

What you will do

• Implement and extend core driver abstractions — Device, Context, Queue, Memory, Function (kernel representation and launch) — across diverse hardware backends, including bindings that expose vendor-specific functionality where it matters.
• Contribute to multi-accelerator and multi-node communication and collectives primitives that underpin large-model inference, using technologies like NVLink, RDMA (Infiniband, RoCE, EFA), and sockets — via a combination of direct programming and broker libraries like UCX.
• Improve diagnostics and error reporting across our asynchronous execution stack — turning low-level driver failures into actionable messages for kernel and graph authors in production environments.
• Partner with peer teams — Kernels, Graph Compiler/Runtime, and Serving — to build and refine the surfaces they consume in the Mojo standard library and MAX framework.
• Participate in design discussions, code reviews, and collaborative software development to uphold high engineering standards.
• Contribute to a fully open source project — everything you build will be public and part of our GitHub repo.

What you bring to the table

• 3+ years of experience writing high-performance, low-latency production systems C++ (modern C++17/20), with strong instincts for ownership, lifetime, ABI stability, concurrency, and parallelism.
• Hands-on experience with at least one accelerator driver-level API — CUDA Driver API, HIP, Metal, or Vulkan compute — including streams, events, contexts, and module loading. Familiarity with async allocators and IPC is a plus.
• Working understanding of accelerator execution and memory models — stream ordering, host↔device transfers, and pinned memory. Exposure to peer access and multi-GPU topologies (NVLink/xGMI, NUMA) is a plus.
• Solid instincts for library and API design — naming, layering, ergonomics.
• Strong debugging skills in asynchronous, multi-device systems — GDB/LLDB, sanitizers, CUDA/HIP error modes, race conditions, leaked resources.
• A proactive, collaborative mindset, intellectual curiosity, and drive to identify and solve complex technical challenges as part of a high-performing team.

Helpful but not required

• Experience with asynchronous runtimes, custom memory allocators, or RDMA-based networking (Infiniband, RoCE, EFA, UCX, NIXL, MPI, NVSHMEM/ROCSHMEM/OpenSHMEM).
• Exposure to non-NVIDIA accelerators in production — AMD ROCm, Apple Metal, etc.
• Experience with zero-copy tensor interoperability — DLPack, the CUDA Array Interface, or similar.
• Familiarity with Mojo, or recent open-source contributions to systems projects (LLVM, PyTorch, JAX/XLA, TVM, IREE, vLLM, TRT-LLM).
• An advanced degree in Computer Science or a related field.

What Modular brings to the table:

• Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
• World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location.
• Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce. 
• Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles.